Multi‐objective framework for structural model identification

Structural identification based on measured dynamic data is formulated in a multi‐objective context that allows the simultaneous minimization of the various objectives related to the fit between measured and model predicted data. Thus, the need for using arbitrary weighting factors for weighting the relative importance of each objective is eliminated. For conflicting objectives there is no longer one solution but rather a whole set of acceptable compromise solutions, known as Pareto solutions, which are optimal in the sense that they cannot be improved in any objective without causing degradation in at least one other objective. The strength Pareto evolutionary algorithm is used to estimate the set of Pareto optimal structural models and the corresponding Pareto front. The multi‐objective structural identification framework is presented for linear models and measured data consisting of modal frequencies and modeshapes. The applicability of the framework to non‐linear model identification is also addressed. The framework is illustrated by identifying the Pareto optimal models for a scaled laboratory building structure using experimentally obtained modal data. A large variability in the Pareto optimal structural models is observed. It is demonstrated that the structural reliability predictions computed from the identified Pareto optimal models may vary considerably. The proposed methodology can be used to explore the variability in such predictions and provide updated structural safety assessments, taking into consideration all Pareto structural models that are consistent with the measured data. Copyright © 2005 John Wiley & Sons, Ltd.     

Improving Properties of Sand Using Epoxy Resin and Electrokinetics

The use of new materials for soil strengthening is crucial for geotechnical engineering, especially in foundation construction. The main objective of this study was to investigate the potential use of two-component water-soluble epoxy resin to improve the physical and mechanical properties of medium sand, because the efficacy of these resins on soil strengthening has not yet been properly investigated. The experiments were conducted using resins with different epoxy resin-to-water ratios. The results of this study indicate that the epoxy resins improve the physical and mechanical properties of the sand significantly, and if successfully grouted into a formation, the resins could provide a suitable solution for the stabilization of the foundation material. In separate experiments, electroosmotic treatment of sand/resin mixtures was conducted with the aim of identifying the effectiveness of electro kinetic method on the early strength development of sand/resin mixtures. From the results it was observed that the electroosmotically treated specimens appeared to have much greater strength enhancement than the one of the untreated specimens.     

A hybrid optimization scheme for self-potential measurements due to multiple sheet-like bodies in arbitrary 2D resistivity distributions

Self-potential is a passive geophysical method that can be applied in a straightforward manner with minimum requirements in the field. Nonetheless, interpretation of self-potential data is particularly challenging due to the inherited non-uniqueness present in all potential methods. Incorporating information regarding the target of interest can facilitate interpretation and increase the reliability of the final output. In the current paper, a novel method for detecting multiple sheet-like targets is presented. A numerical framework is initially described that simulates sheet-like bodies in an arbitrary 2D resistivity distribution. A scattered field formulation based on finite differences is employed that allows the edges of the sheet to be independent of the grid geometry. A novel analytical solution for two-layered models is derived and subsequently used to validate the accuracy of the proposed numerical scheme. Lastly, a hybrid optimization is proposed that couples linear least-squares with particle-swarm optimization in order to effectively locate the edges of multiple sheet-like bodies. Through numerical and real data, it is proven that the hybrid optimization overcomes local minimal that occurs in complex resistivity distributions and converges substantially faster compared to traditional particle-swarm optimization.     

Model evaluation of the atmospheric boundary layer and mixed-layer evolution

In the present study, an attempt is made to assess the atmospheric boundary-layer (ABL) depth over an urban area, as derived from different ABL schemes employed by the mesoscale model MM5. Furthermore, the relationship of the mixing height, as depicted by the measurements, to the calculated ABL depth or other features of the ABL structure, is also examined. In particular, the diurnal evolution of ABL depth is examined over the greater Athens area, employing four different ABL schemes plus a modified version, whereby urban features are considered. Measurements for two selected days, when convective conditions prevailed and a strong sea-breeze cell developed, were used for comparison. It was found that the calculated eddy viscosity profile seems to better indicate the mixing height in both cases, where either a deep convective boundary layer develops, or a more confined internal boundary layer is formed. For the urban scheme, the incorporation of both anthropogenic and storage heat release provides promising results for urban applications.     

Implications of sea-level rise for overwash enhancement at South Portugal

Overwash is one of the most prominent hazards affecting coastal zones, and the associated consequences are expected to increase because of both sea-level rise and intensification of coastal occupation. This study used a 23-year data set of wave heights and tide-surge levels to define return periods of overwash potential for current and future sea-level conditions, namely 2055 and 2100, at two sites from South Portugal. A relevant intensification of both frequency and magnitude of the overwash is expected to occur by mid-century if adaptation measures are not taken and further aggravated by 2100. Current overwash levels with a return period of 100-years can reach a return period lower than 20-years by 2055 and 10-years by 2100. However, these values are rather variable from site to site, highlighting the urgency to develop detailed local studies to identify climate change impacts along coastal sectors, based on validated equations and long-term time series. These could be easily carried by replicating and adapting the here proposed methodology to sandy coasts worldwide. Understating the impact that climate change (namely sea-level rise) may have at the local level is key to contribute to effective management plans that include adaptation measures to minimize risks associated with coastal floods.